Searching for data via the internet has become part of the daily life. Since the amount of data which can be accessed by a user over the internet has been steadily increased during the last years, content recommendation systems have been developed which facilitate the process of searching and accessing specific data.
Generally, a content recommendation system works as follows: First, a user is provided with a first selection of content items by the content recommendation system. Second, feedback is given by the user indicating which of the content items of the first selection he likes/dislikes. Third, the content recommendation system generates a second selection of content items based on the feedback given by the user. The second and third step may be repeated several times.
Known content recommendation systems often need a considerable amount of time to generate requested selections of content items. Further, the selections of content items offered by the content recommendation systems may not be satisfying for the user, in particular if the user contacts the recommendation device for the first time and therefore no user profile exists.